Multi-kernel inception aggregation diffusion network for tomato disease detection

Hao Sun, Changying Fan, Xiaomei Gai, Mohammed Abdulhakim Al-Absi, Shiyu Wang, Muhammed Alam, Xuewei Wang, Rui Fu

Research output: Contribution to journalArticlepeer-review

2 Downloads (Pure)

Abstract

Tomato leaf diseases significantly impact the yield and quality of tomatoes during cultivation, the main of which are septoria leaf spot, leaf curl virus, verticillium wilt, and early blight. These diseases necessitate prompt detection and management strategies to mitigate their deleterious effects on crop productivity. Due to the considerable scale variations in diseased tomato leaves, accurate and rapid detection and diagnosis remain challenging. To address the detection of tomato leaf diseases at different scales, we propose a real-time detection model incorporating a Multi-kernel Inception Aggregation Diffusion Network. In this paper, (1) We present a Multi-kernel Inception Aggregation Diffusion Network (MIADN) for the feature processing stage, which facilitates the aggregation and diffusion of multi-scale features across hierarchical levels, benefiting the detection of targets at various scales. (2) We present the Multi-kernel Inception Module (MKIM), designed to extract multi-scale object features using diverse convolution kernels, thereby enhancing the model’s feature fusion and representation capabilities. (3) We incorporate the efficient FasterNet network at the feature extraction stage to preserve feature diversity and improve the model’s ability to extract complex target features. (4) Extensive comparative and ablation experiments demonstrate that our method achieves the mean average precision (mAP50) of 96.6%, surpassing the baseline model by 4.1% and the advanced YOLOv9s model by 2.0%. This method provides an effective solution for high-quality tomato cultivation.
Original languageEnglish
Article number1069
Number of pages12
JournalBMC Plant Biology
Volume24
Issue number1
Early online date13 Nov 2024
DOIs
Publication statusE-pub ahead of print - 13 Nov 2024

Keywords

  • Multi-kernel inception module
  • Multi-scale detection
  • Multi-kernel inception aggregation diffusion network
  • Deep learning
  • FasterNet
  • Tomato disease detection

Cite this